Build and deploy predictive models for operational planning and execution (e.g., cycle time, throughput, labor/time estimation, service levels)
Develop and improve optimization and decision algorithms (e.g., routing, replenishment, inventory positioning, parameter estimation)
Design experiments and evaluation frameworks to validate impact (accuracy, latency, cost reduction, productivity lift)
Translate business workflows into model-ready problem statements, features, and measurable success criteria
Partner with software engineers to ensure solutions are production-ready (reliable inference, monitoring, versioning, performance tuning)
Create clear documentation and stakeholder-ready summaries of methodology, assumptions, and results
Contribute to architecture and scaling decisions for data/ML solutions (performance, robustness, and maintainability)

3+ years in data science / applied research / analytics engineering (or equivalent), delivering models or algorithms used in real workflows
Demonstrated experience in at least one of:
Applied ML for operational prediction (time, demand, performance, risk)
Operations research / optimization (routing, scheduling, inventory, network/warehouse optimization)
Simulation-based analysis for operational decision-making
Comfortable working cross-functionally and driving work from problem definition through delivery

We pride ourselves in our family-like culture and casual, but focused, work environment
We offer competitive salaries and health benefits
Our 401K program includes a 100% match up to 5%
Participation in our Discretionary Profit-Sharing Program
We offer our employees flexibility and autonomy
We do community outreach projects throughout the year
We know how to throw company events
We work hard, but we also know how to have fun
darts, anyone?

Data Scientist

Key skills